Covid Report for Family

Background

Notes and format last updated Apr 16, 2020

• This page shows COVID data broken down into regions that affect our family. It pulls from publicly available raw data from the NY Times, which is reported daily. It’s on a one-day lag, so when you see this report, the most recent day included will be that reported the day prior.
• The table of contents above summarizes the major sections and can be used to jump to those sections.
• Each major section is then divided into tabs to allow you to more easily shuffle between geographies and metrics.
  • If you open on your phone, I don’t believe the tabs will work, so you’ll just see the page as one long, continuous document.
• More detailed descriptions and context can be found in each section.

Growth rates

Heat maps

• The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
• The first plot compares growth rate for total cases; the second, growth rate for total deaths.
• The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
• The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
  • You can use the plots to track each geography over time and to compare the geographies to one another.
  • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines using rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
  • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
  • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines using rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
  • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
  • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

• This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
• For each metric, in addition to the tables, the trends for the top states are plotted over time.
  • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)

Ranking	State	Cases Per Million
1	New York	15,171
2	New Jersey	12,818
3	Massachusetts	8,458
4	Rhode Island	7,481
5	Connecticut	7,380
6	Louisiana	5,869
7	District of Columbia	5,659
8	Delaware	4,698
9	Michigan	3,928
10	Illinois	3,795
11	Pennsylvania	3,540
12	Maryland	3,326
13	South Dakota	2,615
14	Colorado	2,472
15	Indiana	2,463
16	Georgia	2,223
17	Mississippi	2,130
18	Iowa	2,020
19	Nebraska	1,867
20	Washington	1,846
21	Virginia	1,679
22	Nevada	1,562
23	Florida	1,528
24	New Hampshire	1,478
25	Tennessee	1,468
26	Ohio	1,434
27	New Mexico	1,418
28	Vermont	1,381
29	Alabama	1,376
30	Utah	1,354
31	North Dakota	1,300
32	Kansas	1,231
33	Missouri	1,207
34	California	1,178
35	South Carolina	1,113
36	Wisconsin	1,080
37	Arkansas	1,036
38	Idaho	1,012
39	Kentucky	979
40	Arizona	954
41	Texas	926
42	North Carolina	912
43	Oklahoma	861
44	Maine	773
45	Minnesota	741
46	Wyoming	684
47	West Virginia	610
48	Oregon	565
49	Alaska	477
50	Puerto Rico	438
51	Hawaii	425
52	Montana	421

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Cases Per Million
1	Delaware	341
2	New Jersey	312
3	Rhode Island	250
4	Massachusetts	239
5	New York	222
6	Illinois	166
7	Connecticut	161
8	District of Columbia	139
9	Iowa	133
10	Maryland	129
11	Nebraska	122
12	Indiana	108
13	Pennsylvania	96
14	North Dakota	82
15	Virginia	77
16	Colorado	73
17	Mississippi	69
18	Michigan	68
19	South Dakota	62
20	Kansas	57
21	Louisiana	55
22	New Hampshire	53
23	Tennessee	51
24	New Mexico	49
25	Georgia	43
26	Minnesota	43
27	Utah	40
28	Alabama	36
29	Kentucky	35
30	Wisconsin	34
31	California	33
32	Ohio	33
33	North Carolina	32
34	Florida	31
35	Missouri	31
36	South Carolina	31
37	Arizona	30
38	Nevada	29
39	Texas	27
40	Washington	25
41	Arkansas	24
42	Wyoming	19
43	Oklahoma	18
44	West Virginia	13
45	Maine	12
46	Oregon	10
47	Vermont	10
48	Idaho	9
49	Puerto Rico	9
50	Alaska	5
51	Hawaii	1
52	Montana	1

Total deaths

Table of total deaths per million residents (all 50 states)

Ranking	State	Deaths Per Million
1	New York	906
2	New Jersey	725
3	Connecticut	585
4	Massachusetts	457
5	Louisiana	378
6	Michigan	357
7	District of Columbia	269
8	Rhode Island	225
9	Illinois	168
10	Pennsylvania	163
11	Maryland	153
12	Delaware	140
13	Indiana	133
14	Colorado	127
15	Washington	104
16	Georgia	96
17	Mississippi	80
18	Vermont	75
19	Nevada	73
20	Ohio	68
21	Virginia	57
22	Florida	54
23	Minnesota	53
24	Missouri	52
25	New Mexico	52
26	Oklahoma	52
27	Kentucky	51
28	Wisconsin	51
29	Alabama	49
30	California	47
31	New Hampshire	44
32	Iowa	43
33	Kansas	43
34	Arizona	40
35	Maine	37
36	South Carolina	37
37	Idaho	33
38	North Carolina	33
39	Nebraska	29
40	Tennessee	28
41	Texas	25
42	North Dakota	24
43	Oregon	23
44	West Virginia	21
45	Arkansas	18
46	Puerto Rico	16
47	Montana	14
48	Utah	14
49	South Dakota	12
50	Wyoming	12
51	Hawaii	11
52	Alaska	9

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Deaths Per Million
1	Connecticut	21
2	New Jersey	21
3	Massachusetts	20
4	New York	17
5	District of Columbia	11
6	Michigan	9
7	Delaware	8
8	Louisiana	8
9	Maryland	7
10	Rhode Island	7
11	Illinois	6
12	Pennsylvania	6
13	Indiana	5
14	Colorado	3
15	Georgia	3
16	Minnesota	3
17	Iowa	2
18	Mississippi	2
19	Missouri	2
20	Nevada	2
21	New Mexico	2
22	Ohio	2
23	Virginia	2
24	Washington	2
25	Alabama	1
26	Arizona	1
27	California	1
28	Florida	1
29	Kentucky	1
30	North Carolina	1
31	North Dakota	1
32	Oklahoma	1
33	South Carolina	1
34	Wisconsin	1
35	Alaska	0
36	Arkansas	0
37	Hawaii	0
38	Idaho	0
39	Kansas	0
40	Maine	0
41	Montana	0
42	Nebraska	0
43	New Hampshire	0
44	Oregon	0
45	Puerto Rico	0
46	South Dakota	0
47	Tennessee	0
48	Texas	0
49	Utah	0
50	Vermont	0
51	West Virginia	0
52	Wyoming	0

Counties

• This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
  • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
• In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Cases Per Million	Raw Ranking	Percentile
New York	New York	99,679	1	99
Lincoln	Arkansas	57,970	2	99
Bledsoe	Tennessee	39,100	3	99
Rockland	New York	35,155	4	99
Marion	Ohio	33,660	5	99
Davidson	Tennessee	3,728	202	93
Richland	South Carolina	2,078	449	85
Pierce	Washington	1,534	630	79
Orange	California	692	1269	59
York	South Carolina	669	1301	58

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Deaths Per Million	Raw Ranking	Percentile
New York	New York	7,409	1	99
Randolph	Georgia	2,803	2	99
Terrell	Georgia	2,110	3	99
Nassau	New York	1,503	4	99
Early	Georgia	1,472	5	99
Pierce	Washington	56	672	78
Richland	South Carolina	51	715	77
Davidson	Tennessee	36	893	71
Orange	California	13	1244	60
York	South Carolina	11	1296	58

Our county percentiles over time

Raw counts

• This section shows the raw counts over time for the U.S., our states, and our counties for four categories:
  • Total confirmed cases: This is the cumulative total of cases reported.
  • New confirmed cases: This is the number of new cases reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new cases, to help better visualize the peak.
  • Total deaths: This is the cumulative total of deaths reported.
  • New deaths: This is the number of new deaths reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new deaths, to help better visualize the peak.

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons

• This section is a work in progress. It’s exploring what effect stay-at-home orders have on spread. It’s inherentely messy because some states have localized orders but not orders for their full state and because states implemented the orders at different times.
  • The first plot shows a rolling 3-day average of new cases per million residents, averaged across 2 groups of states – those with a state-wide stay-at-home order in effect and those without. The size of the dots reflect the number of states in each group for each given day (so the dots are getting bigger over time for the group with orders, as more states implement those orders).
    • So far, this view doesn’t show if these orders are “working” or not. Instead, the biggest takeaway from the current plot is that the states that implemented orders are reacting to having worse spread, which is why the case rate is so much higher at the start for them. As a state decides it has a problem and implements an order, it joins the grouping of states with orders and drives the rate up for that group.
    • Over time (if the policies work), what we’d expect is that the line for the group with orders flattens or declines in relation to the no-order group. It also may become moot if all states issue orders.
    • As states start rescending their orders, I’ll put them back into the no-order group, so the no-order group should beging to expand again.
  • The second plot tracks progress of states by the number of days since orders have been in effect. It includes only those states with orders and shows their average new case growth rate (a rolling 3-day average of daily growth rates) based on how long it’s been since the order went into effect. Again, the size of the dots show how many states are included in each point – i.e., as you go further right, the dots are smaller because less states are that far past their order.
    • I’m working on how to add a baseline to this chart to compare to states without orders, but that’s challenging because there’s no way to fully align timing.